Visual place recognition based self-localization for autonomous vehicles
First Claim
1. An autonomous vehicle control system, comprising:
- a processor in communication with a sensor, the sensor sensing an environment surrounding a vehicle associated with the vehicle control system, wherein a feature vector describes at least a portion of the environment at a current location of the vehicle on a route, the processor being programmed to;
receive view image information from the sensor comprising the feature vector;
extract extraneous information from the received view image information, wherein the extraneous information comprises view information other than the feature vector, and wherein extracting the extraneous information isolates the feature vector;
retrieve feature vector information associated with one or more segments of a route of travel for the vehicle;
compare the isolated feature vector to the retrieved feature vector information;
determine if the isolated feature vector and the retrieved feature vector information match; and
if the isolated feature vector and the retrieved feature vector information match, determine that the current location of the vehicle is at a segment location of the one or more segments associated with the retrieved feature vector information.
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Abstract
Methods and systems herein can let an autonomous vehicle localize itself precisely and in near real-time in a digital map using visual place recognition. Commercial GPS solutions used in the production of autonomous vehicles generally have very low accuracy. For autonomous driving, the vehicle may need to be able to localize in the map very precisely, for example, within a few centimeters. The method and systems herein incorporate visual place recognition into the digital map and localization process. The roadways or routes within the map can be characterized as a set of nodes, which can be augmented with feature vectors that represent the visual scenes captured using camera sensors. These feature vectors can be constantly updated on the map server and then provided to the vehicles driving the roadways. This process can help create and maintain a diverse set of features for visual place recognition.
1002 Citations
20 Claims
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1. An autonomous vehicle control system, comprising:
a processor in communication with a sensor, the sensor sensing an environment surrounding a vehicle associated with the vehicle control system, wherein a feature vector describes at least a portion of the environment at a current location of the vehicle on a route, the processor being programmed to; receive view image information from the sensor comprising the feature vector; extract extraneous information from the received view image information, wherein the extraneous information comprises view information other than the feature vector, and wherein extracting the extraneous information isolates the feature vector; retrieve feature vector information associated with one or more segments of a route of travel for the vehicle; compare the isolated feature vector to the retrieved feature vector information; determine if the isolated feature vector and the retrieved feature vector information match; and if the isolated feature vector and the retrieved feature vector information match, determine that the current location of the vehicle is at a segment location of the one or more segments associated with the retrieved feature vector information. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. An autonomous vehicle control system, comprising
a processor in communication with a sensor, the sensor sensing an environment surrounding a vehicle associated with the vehicle control system, wherein a feature vector describes at least a portion of the environment at a current location of the vehicle on a route, the processor being programmed to: -
receive information from the sensor regarding the feature vector; retrieve feature vector information associated with one or more segments of a route of travel for the vehicle; compare the received feature vector to the retrieved feature vector information, determine if the received feature vector and the retrieved feature vector information match; if the received feature vector and the retrieved feature vector information match, determine that the current location of the vehicle is at a segment location of the one or more segments associated with the retrieved feature vector information; determine, after determining the segment location, a new feature vector in view of the sensor; characterize the new feature vector; and provide the new feature vector to another vehicle to aid the other vehicle in determining the location at the segment. - View Dependent Claims (12, 13)
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14. A method comprising:
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determining, by a processor, a preliminary location of a vehicle on a route of travel, wherein the route of travel is delineated into two or more segments; receiving, by the processor, view image information, from a sensor, wherein the sensor senses an environment surrounding the vehicle, wherein the view image information comprises a feature vector, wherein the feature vector describes at least a portion of the environment surrounding the vehicle at a current location of the vehicle; extracting, by the processor, extraneous information from the received view image information, wherein the extraneous information comprises view information other than the feature vector, and wherein extracting the extraneous information isolates the feature vector; retrieving feature vector information associated with the one or more segments of the route of travel for the vehicle; comparing the isolated feature vector and the retrieved feature vector information; determining if the isolated feature vector and the retrieved feature vector information match; and if the isolated feature vector and the retrieved feature vector information match, determining that the current location of the vehicle is at a segment location of the segment associated with the retrieved feature vector information. - View Dependent Claims (15, 16, 17, 18, 19, 20)
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Specification